Modeling the Impact on Sediment Texture of Large-Scale Tidal Power in the Bay of Fundy
Bibliographic record
Abstract
The output of a 3-D ocean circulation model and information on nearly 10,000 sediment\nsamples are used to examine the extent to which a model of ocean currents can be used to predict seabed sediment texture in the Bay of Fundy and Gulf of Maine. It is found that sediment texture is generally closer to equilibrium with maximum tidal bed shear stress in the Gulf of Maine than in the Bay of Fundy. In the Bay of Fundy, competent mean grain sizes are generally coarser than observed mean grain sizes, and further interpretation suggests that sediment supply has a dominant influence on texture. Furthermore, the impact on texture is predicted for two tidal power development scenarios in the Minas Passage (Hasegawa et al., 2011). For a 2.0 GW of power scenario, a sediment fining is predicted in parts of Minas Passage, although the impact should be small as supply dominates texture. Further research is needed to quantify with more precision the potential impact of tidal power development on texture, especially in the Bay of Fundy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".